Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A system, comprising: a broker module, executing on at least one server computer, the broker module configured to be coupled to a plurality of vendor-specific computing environments for receiving parameters associated with characteristics of the vendor-specific computing environments, the broker module further configured to receive application parameters, and to determine which of the plurality of vendor-specific environments is suitable for hosting an application associated with the application parameters, wherein the application parameters include an indication that the application is to be hosted simultaneously on two different vendor-specific environments of the plurality of vendor-specific environments, wherein the vendor-specifice environments that are determined by the broker module to be suitable for hosting the application includes a first vendor-specific environment and a second vendor-specific environment, and wherein the broker module is further configured to communicate to a client system a notification indicating the determined first and second vendor-specific environments.
This invention relates to a system for selecting and managing multi-vendor cloud computing environments for hosting applications. The problem addressed is the complexity of determining suitable cloud environments across different vendors while ensuring applications can be deployed across multiple vendors simultaneously. The system includes a broker module running on a server that connects to multiple vendor-specific cloud environments. The broker collects parameters describing the characteristics of each vendor's environment, such as performance, cost, and compatibility, and also receives application-specific parameters. These parameters define the application's requirements, including the need to be hosted on two different vendor environments at the same time. The broker evaluates the vendor environments to identify a suitable pair, such as a first and second vendor environment, that meet the application's needs. Once identified, the broker notifies a client system of the selected environments, enabling the application to be deployed across both. This approach simplifies multi-vendor cloud deployment by automating the selection process and ensuring compatibility across different vendor platforms.
2. The system of claim 1 , wherein the characteristics of the vendor-specific computing environments include: pricing, capability, framework structure, or performance.
A system for managing vendor-specific computing environments in a cloud or distributed computing context addresses the challenge of efficiently selecting and utilizing diverse vendor platforms. The system evaluates and compares vendor-specific computing environments based on key characteristics such as pricing, capability, framework structure, and performance. By analyzing these factors, the system enables users to optimize resource allocation, cost efficiency, and compatibility with application requirements. The system may integrate with multiple cloud providers or on-premises environments, dynamically assessing their suitability for specific workloads. This allows organizations to make informed decisions when deploying applications, ensuring alignment with performance, budget, and architectural constraints. The system may also support automated recommendations or policy-based enforcement to streamline environment selection and management. By standardizing the evaluation of vendor-specific environments, the system reduces complexity and improves operational efficiency in heterogeneous computing infrastructures.
3. The system of claim 1 , wherein the application parameters include: processor, memory, location of the vendor-specific computing environment, average latency, or pricing.
A system for managing computing resources in a distributed environment addresses the challenge of efficiently allocating and optimizing resources across multiple vendor-specific computing environments. The system collects and analyzes application parameters to dynamically assign resources based on performance and cost requirements. Key parameters include processor specifications, memory allocation, the location of the vendor-specific computing environment, average latency, and pricing. By evaluating these factors, the system ensures optimal resource utilization, minimizing latency and cost while maintaining performance. The system may also integrate with multiple vendor platforms, allowing seamless resource allocation across different cloud providers or on-premises environments. This approach enables users to deploy applications with the most suitable resources, improving efficiency and reducing operational expenses. The system dynamically adjusts resource allocation in response to changing workload demands, ensuring consistent performance and cost-effectiveness. Additionally, the system may provide insights into resource usage patterns, helping users optimize their computing infrastructure over time.
4. The system of claim 1 , further including a client interface configured to receive, from a client system, the application and the application parameters associated with the application.
A system for managing and executing applications in a distributed computing environment addresses the challenge of efficiently deploying and running applications across multiple computing resources. The system includes a distributed computing environment with multiple computing nodes, each capable of executing applications. A controller manages the execution of applications by distributing tasks to the computing nodes based on workload requirements. The system also includes a client interface that allows a client system to submit applications along with their associated parameters. These parameters define how the application should be executed, such as resource allocation, scheduling preferences, and dependencies. The client interface ensures that the application and its parameters are properly received and processed by the system, enabling seamless integration and execution in the distributed environment. This approach optimizes resource utilization and improves application performance by dynamically allocating tasks across available computing nodes.
5. The system of claim 4 , wherein the client interface is further configured to: communicate a request, to the client system, for approval to host the application in one of the plurality of vendor-specific computing environments, wherein the request includes a vendor identity.
A system for managing application deployment in vendor-specific computing environments addresses the challenge of securely and efficiently hosting applications across multiple cloud or on-premises platforms. The system includes a client interface that facilitates communication between a client system and a deployment management module. The client interface is configured to send a request to the client system, seeking approval to host an application in one of several vendor-specific computing environments. This request includes a vendor identity, allowing the client to specify or confirm the target environment for deployment. The deployment management module processes the request, ensuring compatibility and security requirements are met before proceeding with the deployment. The system may also include a configuration module that standardizes application settings across different vendor environments, reducing manual configuration efforts. Additionally, a monitoring module tracks application performance and resource usage in the deployed environment, providing feedback to optimize deployment strategies. The system streamlines the deployment process while maintaining control over where and how applications are hosted, addressing the complexity of managing multi-vendor cloud or hybrid environments.
6. The system of claim 1 , wherein the broker module is further configured to receive an indication to not host the application using one of the plurality of vendor-specific computing environments.
A system for managing application deployment across multiple vendor-specific computing environments addresses the challenge of efficiently allocating applications to optimal cloud or on-premises environments while avoiding vendor lock-in. The system includes a broker module that evaluates application requirements and available vendor-specific environments to determine the most suitable deployment option. This module assesses factors such as cost, performance, compliance, and compatibility to select the best environment for hosting the application. The broker module is further configured to receive an indication to exclude certain vendor-specific environments from consideration when deploying an application. This exclusion feature allows users to manually override automated recommendations, ensuring flexibility in deployment decisions. For example, if a particular vendor's environment is deemed unsuitable due to security concerns, compliance restrictions, or cost constraints, the system can be instructed to avoid that environment entirely. This capability enhances control over deployment strategies while maintaining the system's ability to optimize application placement across remaining available environments. The system thus provides a balanced approach to cloud and on-premises deployment, combining automation with user-directed exclusions to meet diverse operational needs.
7. The system of claim 6 , wherein the broker module is configured to move the application from one of the plurality of vendor-specific computing environments to another of the plurality of vendor-specific computing environments in response to the indication.
This invention relates to a system for managing applications across multiple vendor-specific computing environments, such as cloud platforms. The problem addressed is the difficulty of migrating applications between different vendor environments due to compatibility issues, proprietary dependencies, and operational disruptions. The system includes a broker module that facilitates seamless application migration. The broker module monitors application performance and resource usage, detecting conditions that may require relocation, such as cost inefficiencies, performance degradation, or vendor-specific limitations. When a migration is needed, the broker module initiates the transfer of the application from one vendor environment to another, ensuring minimal downtime and maintaining service continuity. The system also includes a compatibility layer that abstracts vendor-specific configurations, allowing the application to operate consistently across different environments. Additionally, the broker module may optimize resource allocation and cost management during and after migration. The invention enables dynamic application mobility, reducing vendor lock-in and improving operational flexibility.
8. A method, comprising: receiving, in a broker module, an application and an application parameter associated with a desired characteristic of an environment in which the application is to be executed; receiving, in the broker module, a plurality of vendor-specific parameters for vendor-specific computing environments; selecting, by the broker module, one of the vendor-specific computing environments based on a match found in one of the plurality of vendor-specific parameters and the application parameter, which indicates that the application is to be executed on two of the vendor-specific computing environments simultaneously; communicating a request to a client interface for approval of the selected vendor-specific computing environment; and responsive to receiving approval of the selected vendor-specific computing environments, initiating simultaneous hosting of the application using the selected vendor-specific computing environments.
The invention relates to a system for deploying applications across multiple vendor-specific computing environments. The problem addressed is the need to efficiently select and manage the execution of applications in environments that require simultaneous operation across different vendor-specific platforms. The method involves a broker module that receives an application and its associated parameters, which define the desired characteristics of the execution environment. The broker module also receives vendor-specific parameters for various computing environments. It then selects a vendor-specific environment by matching the application parameters with the vendor-specific parameters, ensuring the application can run on two different vendor-specific environments at the same time. Once a suitable environment is identified, the broker module sends a request to a client interface for approval. Upon receiving approval, the broker module initiates the simultaneous hosting of the application across the selected vendor-specific environments. This approach ensures compatibility and optimal performance by leveraging multiple vendor-specific platforms in parallel.
9. The method of claim 8 , further including receiving an indication to not host the application using the selected vendor-specific computing environment, which is a first vendor-specific computing environment; and determining, in response to receiving the indication to not host the application using the first vendor-specific computing environment, a second vendor-specific computing environment from the vendor-specific computing environments for hosting the application.
This invention relates to a system for dynamically selecting and managing vendor-specific computing environments for hosting applications. The problem addressed is the need for flexibility in deploying applications across different vendor-specific environments, such as cloud platforms, without being locked into a single vendor's infrastructure. The system allows users to initially select a first vendor-specific computing environment for hosting an application. If the user later decides not to use that environment, the system automatically determines and selects a second vendor-specific computing environment from available options for hosting the application. This ensures continuity of service while providing the flexibility to switch vendors as needed. The system may also include steps for evaluating the suitability of different vendor-specific environments based on factors such as cost, performance, or compliance requirements. The invention aims to streamline the process of migrating applications between vendor-specific environments, reducing downtime and operational disruptions.
10. The method of claim 8 , wherein the application parameter is associated with cost information associated with hosting the application in the selected vendor-specific computing environment.
This invention relates to optimizing application deployment in cloud computing environments by selecting vendor-specific computing environments based on application parameters and cost information. The method involves analyzing an application to determine its parameters, such as resource requirements, performance metrics, or compatibility constraints. These parameters are then used to identify a suitable vendor-specific computing environment from multiple available options. The selection process considers cost information associated with hosting the application in each environment, ensuring that the chosen environment meets the application's needs while minimizing expenses. The method may also involve dynamically adjusting the selected environment based on changes in application parameters or cost factors. This approach helps users efficiently deploy applications in cloud environments by balancing performance, compatibility, and cost considerations. The invention addresses the challenge of selecting the most cost-effective and suitable cloud environment for an application, particularly in multi-vendor scenarios where different providers offer varying pricing models and capabilities.
11. The method of claim 8 , wherein an application owner overrides the selection of the vendor-specific computing environment made by the broker module.
A system and method for managing computing environments in a multi-vendor cloud infrastructure addresses the challenge of efficiently allocating workloads across diverse vendor-specific environments while ensuring optimal performance and cost efficiency. The system includes a broker module that evaluates workload requirements and selects an appropriate vendor-specific computing environment based on predefined criteria such as cost, performance, and compatibility. The broker module dynamically assigns workloads to the selected environment to balance resource utilization and minimize operational costs. An application owner can override the broker module's selection of the vendor-specific computing environment. This override capability allows the owner to manually specify a preferred environment, ensuring compliance with organizational policies, regulatory requirements, or specific performance needs. The override function provides flexibility in workload management, enabling the application owner to prioritize certain environments despite the broker module's automated recommendations. This feature is particularly useful in scenarios where the broker module's selection may not align with business objectives or technical constraints. The system ensures seamless integration between automated and manual decision-making processes, enhancing overall control and adaptability in cloud resource management.
12. The method of claim 8 , wherein the application parameter identifies acceptable values of a central processing unit, a memory, a physical location of the vendor-specific computing environment, security minimums, or hosting costs.
This invention relates to a method for managing application deployment in vendor-specific computing environments. The problem addressed is the lack of standardized criteria for selecting and configuring computing environments to meet application requirements, leading to inefficiencies in deployment, security risks, and cost mismanagement. The method involves defining application parameters that specify acceptable values for various computing environment attributes. These parameters include central processing unit (CPU) specifications, memory requirements, physical location constraints of the vendor-specific environment, security minimums, and hosting costs. By evaluating these parameters, the method ensures that the selected computing environment meets the application's technical and operational needs. The method also includes a step of validating the computing environment against the defined parameters before deployment. This validation step helps prevent compatibility issues, security vulnerabilities, and cost overruns. Additionally, the method may involve dynamically adjusting the parameters based on real-time performance data or changes in application requirements. The invention improves the reliability and efficiency of application deployment by providing a structured approach to selecting and validating computing environments. It ensures that applications are deployed in environments that meet predefined technical, security, and cost criteria, reducing the risk of failures and optimizing resource utilization.
13. The method of claim 8 , wherein the vendor-specific parameters identify the following in the vendor-specific computing environments: a central processing unit, a memory, a physical location of the vendor-specific computing environment, security minimums, or hosting costs.
This invention relates to managing vendor-specific computing environments by identifying and utilizing vendor-specific parameters to optimize resource allocation and deployment. The problem addressed is the lack of standardized parameters across different vendor environments, which complicates the deployment and management of computing resources. The solution involves a method that extracts and processes vendor-specific parameters to tailor computing environments to specific requirements. The method includes identifying and storing vendor-specific parameters that define characteristics of the computing environment, such as the central processing unit (CPU), memory, physical location, security minimums, and hosting costs. These parameters are used to configure and deploy computing resources in a way that aligns with the vendor's capabilities and constraints. By analyzing these parameters, the system can determine the optimal configuration for workloads, ensuring efficient resource utilization and cost-effectiveness. The method also involves dynamically adjusting the computing environment based on changes in vendor-specific parameters, such as fluctuations in hosting costs or security requirements. This ensures that the environment remains compliant and cost-efficient over time. The approach allows for seamless integration with multiple vendor environments, providing flexibility and scalability in deploying computing resources.
14. A computer-readable storage medium including instructions that upon execution cause a computer system to: receive, using one or more processors of a server computer hosting a broker module, application parameters associated with an application, the application parameters defining constraints on a computing environment for hosting the application, the application parameters indicating that the application is to be simultaneously launched in at least two vendor-specific computing environments; receive, using the one or more processors of the server computer hosting the broker module, vendor-specific data associated with vendor-specific computing environments; determine, using the one or more processors of the server computer hosting the broker module, which of the vendor-specific computing environments matches the application parameters; select at least two of the vendor-specific computing environments determined to match the application parameters; and initiate simultaneous hosting of the application using each of the selected vendor-specific computing environments.
This invention relates to a system for deploying applications across multiple vendor-specific computing environments. The problem addressed is the need to launch an application simultaneously in different vendor-specific environments while ensuring compatibility with predefined constraints. The system uses a broker module hosted on a server to receive application parameters that define requirements for the computing environment, such as resource limits, dependencies, or compatibility rules. These parameters specify that the application must be launched in at least two distinct vendor-specific environments. The broker module also receives vendor-specific data describing the capabilities and configurations of available computing environments. By comparing the application parameters with the vendor-specific data, the system identifies which environments meet the requirements. The broker then selects at least two compatible environments and initiates the simultaneous deployment of the application in each. This ensures the application runs in multiple vendor-specific environments without manual intervention, improving reliability and reducing deployment complexity. The system automates the selection and launch process, ensuring consistency across different vendor platforms.
15. The computer-readable storage medium of claim 14 , wherein the instructions, upon execution, further cause the computer system to: receive updated application parameters in the one or more processors of the server computer hosting the broker module; based on the updated application parameters, terminate the application on the vendor-specific computing environment and select a different vendor-specific computing environment that matches the updated application parameters; and launch the application on the selected different vendor-specific computing environment.
This invention relates to a system for dynamically managing application deployment in a multi-vendor cloud computing environment. The problem addressed is the need to efficiently adapt application deployments to changing requirements, such as performance, cost, or compatibility constraints, without manual intervention. The system includes a broker module that monitors application parameters and selects the most suitable vendor-specific computing environment (e.g., cloud provider) based on those parameters. The broker module can terminate an application running in one vendor's environment and automatically redeploy it in a different environment that better matches updated parameters, ensuring optimal performance and resource utilization. The system supports seamless transitions between vendors, allowing applications to adapt to evolving needs without downtime or manual configuration. This approach improves flexibility and cost-efficiency in cloud deployments by dynamically aligning applications with the best available vendor-specific infrastructure.
16. The computer-readable storage medium of claim 14 , wherein the application parameters include a desired cost for hosting the application.
A system and method for optimizing cloud application deployment involves dynamically adjusting cloud resources based on application performance metrics and cost constraints. The technology addresses the challenge of efficiently managing cloud-hosted applications by balancing performance requirements with cost considerations. The system monitors application performance metrics such as response time, throughput, and resource utilization. Based on these metrics, it automatically scales cloud resources up or down to maintain desired performance levels while minimizing hosting costs. The system also incorporates application parameters, including a specified cost threshold for hosting the application. When the actual or projected hosting cost exceeds this threshold, the system adjusts resource allocation to reduce costs, potentially by downgrading hardware specifications, reducing the number of active instances, or migrating to lower-cost cloud regions. The system may also predict future resource needs and preemptively adjust allocations to avoid performance degradation or cost overruns. The solution ensures that applications remain performant while adhering to budget constraints, making it suitable for businesses seeking cost-effective cloud deployment strategies.
17. The computer-readable storage medium of claim 14 , wherein the vendor-specific data includes: a central processing unit, a memory, a physical location of the vendor-specific computing environment, security minimums, or hosting costs.
This invention relates to a system for managing vendor-specific computing environments, addressing challenges in tracking and utilizing vendor-specific data to optimize resource allocation and decision-making. The system involves storing vendor-specific data in a structured format, such as a database or file, to facilitate analysis and comparison of different computing environments. The data includes details about the central processing unit (CPU), memory, physical location of the computing environment, security requirements, and hosting costs. By organizing this information, the system enables users to evaluate and select the most suitable vendor based on performance, security, and cost factors. The invention also supports dynamic updates to the vendor-specific data, ensuring that the information remains current and relevant for decision-making. Additionally, the system may include a user interface for visualizing and interacting with the stored data, allowing users to filter, sort, and compare different computing environments efficiently. This approach helps organizations streamline vendor selection, reduce costs, and improve overall system performance by leveraging detailed, up-to-date vendor-specific information.
18. The computer-readable storage medium of claim 14 , wherein the instructions, upon execution, further cause the computer system to: receive, in the broker module, the application in an application container.
A system and method for managing software applications in a distributed computing environment addresses the challenge of efficiently deploying, scaling, and monitoring containerized applications. The invention provides a broker module that facilitates the deployment and management of applications within application containers, which are lightweight, isolated execution environments. The broker module receives an application in an application container, ensuring that the application is packaged with all necessary dependencies and configurations. This approach simplifies application deployment by abstracting the underlying infrastructure, allowing applications to run consistently across different computing environments. The broker module may also handle tasks such as resource allocation, load balancing, and health monitoring to ensure optimal performance and reliability. By integrating with container orchestration systems, the invention enables seamless scaling of applications based on demand, improving resource utilization and reducing operational overhead. The system supports various container formats and runtime environments, providing flexibility for developers and administrators. This solution enhances the efficiency of application deployment and management in cloud-native and distributed computing environments.
19. The computer-readable storage medium of claim 14 , wherein the vendor-specific computing environments include hardware for hosting the application.
A system and method for managing vendor-specific computing environments in a cloud-based platform. The technology addresses the challenge of integrating diverse hardware and software configurations from multiple vendors into a unified cloud infrastructure. The system provides a standardized interface for deploying and managing applications across different vendor environments, ensuring compatibility and performance consistency. Each vendor-specific computing environment includes dedicated hardware resources for hosting applications, such as servers, storage, and networking components. The system dynamically allocates these resources based on application requirements, optimizing performance and cost efficiency. Additionally, the system monitors the health and performance of the vendor-specific environments, automatically scaling resources as needed to maintain service levels. This approach simplifies the deployment of applications in multi-vendor cloud environments while reducing operational complexity and improving reliability. The solution is particularly useful for enterprises leveraging hybrid or multi-cloud architectures, where seamless integration of vendor-specific hardware is critical.
20. The computer-readable storage medium of claim 14 , wherein the vendor-specific computing environments are different hardware platforms for hosting the application, wherein the selected vendor-specific computing environments includes a first vendor-specific computing environment and a second vendor-specific computing environment, and wherein, responsive to receiving a user request for the application, the instructions cause the computer system to perform load balancing using one or more load balancing policies and to route the user request to a selected one of the first and second vendor-specific computing environments based on the load balancing.
This invention relates to a system for managing and deploying applications across multiple vendor-specific computing environments, addressing the challenge of efficiently distributing workloads across different hardware platforms. The system provides a computer-readable storage medium containing instructions that enable a computer system to host an application in multiple vendor-specific computing environments, each representing distinct hardware platforms. These environments include at least a first and a second vendor-specific computing environment, allowing the application to operate across diverse hardware configurations. When a user request for the application is received, the system performs load balancing using predefined load balancing policies. These policies determine the optimal routing of the request to either the first or second vendor-specific computing environment based on current workload conditions, ensuring efficient resource utilization and performance. The system dynamically selects the appropriate environment to handle the request, balancing the load across the available hardware platforms to maintain system stability and responsiveness. This approach enhances scalability and reliability by leveraging multiple hardware environments while optimizing performance through intelligent load distribution.
Unknown
October 6, 2020
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